Covid Report for Family

Background

Notes and format last updated Apr 16, 2020

• This page shows COVID data broken down into regions that affect our family. It pulls from publicly available raw data from the NY Times, which is reported daily. It’s on a one-day lag, so when you see this report, the most recent day included will be that reported the day prior.
• The table of contents above summarizes the major sections and can be used to jump to those sections.
• Each major section is then divided into tabs to allow you to more easily shuffle between geographies and metrics.
  • If you open on your phone, I don’t believe the tabs will work, so you’ll just see the page as one long, continuous document.
• More detailed descriptions and context can be found in each section.

Growth rates

Heat maps

• The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
• The first plot compares growth rate for total cases; the second, growth rate for total deaths.
• The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
• The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
  • You can use the plots to track each geography over time and to compare the geographies to one another.
  • You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.

Case growth rates

• This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of cases, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new cases) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines using rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new case reporting at the state level.
  • For total cases, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total cases have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total case line get as close to zero as possible.
  • For new cases, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total cases, we want to watch for the lines for new cases to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis.

U.S.

Our states

Death growth rates

• This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of deaths, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new deaths) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines using rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new death reporting at the state level.
  • For total deaths, the trendlines are a rolling 3-day average of daily growth rates in total deaths. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total deaths have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total death line get as close to zero as possible.
  • For new deaths, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new deaths. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total deaths, we want to watch for the lines for new deaths to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis.

U.S.

Our states

By population rankings

This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.

States

• This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
• For each metric, in addition to the tables, the trends for the top states are plotted over time.
  • We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.

Total confirmed cases

Table of total confirmed cases per million residents (all 50 states)

Ranking	State	Cases Per Million
1	New York	16,266
2	New Jersey	14,269
3	Massachusetts	9,878
4	Rhode Island	8,945
5	Connecticut	8,214
6	District of Columbia	7,107
7	Louisiana	6,311
8	Delaware	5,348
9	Illinois	4,853
10	Michigan	4,379
11	Maryland	4,211
12	Pennsylvania	4,068
13	South Dakota	2,974
14	Indiana	2,960
15	Nebraska	2,939
16	Iowa	2,906
17	Colorado	2,869
18	Georgia	2,601
19	Mississippi	2,536
20	Virginia	2,187
21	Washington	2,045
22	Tennessee	1,893
23	New Hampshire	1,851
24	New Mexico	1,836
25	Nevada	1,776
26	Kansas	1,769
27	Ohio	1,703
28	Florida	1,679
29	Utah	1,614
30	Alabama	1,608
31	North Dakota	1,562
32	Vermont	1,437
33	California	1,393
34	Missouri	1,377
35	Wisconsin	1,367
36	South Carolina	1,286
37	Arizona	1,187
38	Minnesota	1,181
39	Kentucky	1,168
40	Arkansas	1,136
41	Texas	1,113
42	North Carolina	1,112
43	Idaho	1,066
44	Oklahoma	1,003
45	Maine	881
46	Wyoming	751
47	West Virginia	666
48	Oregon	635
49	Puerto Rico	565
50	Alaska	500
51	Hawaii	431
52	Montana	425

New confirmed cases

Table of new cases per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Cases Per Million
1	District of Columbia	327
2	New Jersey	303
3	Massachusetts	284
4	Rhode Island	269
5	Nebraska	233
6	Illinois	225
7	Iowa	213
8	New York	206
9	Maryland	205
10	Delaware	162
11	Connecticut	148
12	Tennessee	115
13	Virginia	110
14	Indiana	104
15	Pennsylvania	100
16	Kansas	98
17	Louisiana	96
18	New Hampshire	91
19	Minnesota	90
20	Mississippi	82
21	Michigan	79
22	Colorado	76
23	New Mexico	69
24	Georgia	68
25	South Dakota	68
26	Wisconsin	63
27	Alabama	55
28	North Dakota	54
29	Ohio	53
30	Utah	52
31	Missouri	48
32	Arizona	45
33	Nevada	45
34	California	38
35	Kentucky	38
36	Washington	38
37	Florida	37
38	Texas	37
39	North Carolina	36
40	South Carolina	34
41	Oklahoma	29
42	Puerto Rico	28
43	Maine	22
44	Arkansas	16
45	Vermont	16
46	Oregon	13
47	West Virginia	13
48	Wyoming	11
49	Idaho	8
50	Alaska	5
51	Hawaii	0
52	Montana	0

Total deaths

Table of total deaths per million residents (all 50 states)

Ranking	State	Deaths Per Million
1	New York	986
2	New Jersey	886
3	Connecticut	683
4	Massachusetts	580
5	Louisiana	423
6	Michigan	405
7	District of Columbia	355
8	Rhode Island	302
9	Pennsylvania	222
10	Illinois	207
11	Maryland	195
12	Delaware	181
13	Indiana	168
14	Colorado	145
15	Georgia	110
16	Washington	110
17	Mississippi	101
18	Ohio	88
19	Nevada	85
20	Vermont	84
21	Virginia	77
22	Minnesota	74
23	New Mexico	72
24	Florida	64
25	New Hampshire	63
26	Missouri	61
27	Oklahoma	60
28	Alabama	59
29	Iowa	58
30	Wisconsin	58
31	Kentucky	57
32	California	56
33	South Carolina	53
34	Arizona	49
35	Kansas	48
36	Maine	42
37	North Carolina	41
38	Nebraska	40
39	Idaho	35
40	North Dakota	32
41	Tennessee	32
42	Texas	30
43	West Virginia	27
44	Arkansas	25
45	Oregon	25
46	South Dakota	23
47	Puerto Rico	16
48	Utah	15
49	Montana	14
50	Hawaii	12
51	Wyoming	12
52	Alaska	9

New deaths

Table of new deaths per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Deaths Per Million
1	New Jersey	24
2	Massachusetts	21
3	Connecticut	16
4	Rhode Island	16
5	New York	14
6	District of Columbia	12
7	Delaware	8
8	Michigan	8
9	Illinois	7
10	Louisiana	7
11	Maryland	7
12	Indiana	6
13	Pennsylvania	6
14	Minnesota	4
15	Mississippi	4
16	New Mexico	4
17	Virginia	4
18	Colorado	3
19	New Hampshire	3
20	Iowa	2
21	Missouri	2
22	Nevada	2
23	North Dakota	2
24	South Carolina	2
25	Vermont	2
26	Alabama	1
27	Arizona	1
28	Arkansas	1
29	California	1
30	Florida	1
31	Georgia	1
32	Kansas	1
33	Kentucky	1
34	Nebraska	1
35	North Carolina	1
36	Ohio	1
37	Oklahoma	1
38	South Dakota	1
39	West Virginia	1
40	Wisconsin	1
41	Alaska	0
42	Hawaii	0
43	Idaho	0
44	Maine	0
45	Montana	0
46	Oregon	0
47	Puerto Rico	0
48	Tennessee	0
49	Texas	0
50	Utah	0
51	Washington	0
52	Wyoming	0

Counties

• This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
  • Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
• In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.

Confirmed cases

Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Cases Per Million	Raw Ranking	Percentile
Trousdale	Tennessee	119,284	1	99
Lincoln	Arkansas	63,114	2	99
Dakota	Nebraska	48,936	3	99
Nobles	Minnesota	43,460	4	99
Bledsoe	Tennessee	39,697	5	99
Davidson	Tennessee	4,359	220	92
Richland	South Carolina	2,319	505	83
Pierce	Washington	1,664	722	77
Orange	California	874	1211	61
York	South Carolina	787	1328	57

Our county percentiles over time

Deaths

Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Deaths Per Million	Raw Ranking	Percentile
Randolph	Georgia	2,803	1	99
Terrell	Georgia	2,227	2	99
Early	Georgia	1,963	3	99
Nassau	New York	1,617	4	99
Essex	New Jersey	1,605	5	99
Richland	South Carolina	96	515	83
Pierce	Washington	57	749	76
Davidson	Tennessee	40	923	70
Orange	California	16	1289	58
York	South Carolina	11	1372	56

Our county percentiles over time

Raw counts

• This section shows the raw counts over time for the U.S., our states, and our counties for four categories:
  • Total confirmed cases: This is the cumulative total of cases reported.
  • New confirmed cases: This is the number of new cases reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new cases, to help better visualize the peak.
  • Total deaths: This is the cumulative total of deaths reported.
  • New deaths: This is the number of new deaths reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new deaths, to help better visualize the peak.

Total confirmed cases

U.S.

Our states

Our counties

New confirmed cases

U.S.

Our states

Our counties

Total deaths

U.S.

Our states

Our counties

New deaths

U.S.

Our states

Our counties

Stay-at-home comparisons

• This section is a work in progress. It’s exploring what effect stay-at-home orders have on spread. It’s inherentely messy because some states have localized orders but not orders for their full state and because states implemented the orders at different times.
  • The first plot shows a rolling 3-day average of new cases per million residents, averaged across 2 groups of states – those with a state-wide stay-at-home order in effect and those without. The size of the dots reflect the number of states in each group for each given day (so the dots are getting bigger over time for the group with orders, as more states implement those orders).
    • So far, this view doesn’t show if these orders are “working” or not. Instead, the biggest takeaway from the current plot is that the states that implemented orders are reacting to having worse spread, which is why the case rate is so much higher at the start for them. As a state decides it has a problem and implements an order, it joins the grouping of states with orders and drives the rate up for that group.
    • Over time (if the policies work), what we’d expect is that the line for the group with orders flattens or declines in relation to the no-order group. It also may become moot if all states issue orders.
    • As states start rescending their orders, I’ll put them back into the no-order group, so the no-order group should beging to expand again.
  • The second plot tracks progress of states by the number of days since orders have been in effect. It includes only those states with orders and shows their average new case growth rate (a rolling 3-day average of daily growth rates) based on how long it’s been since the order went into effect. Again, the size of the dots show how many states are included in each point – i.e., as you go further right, the dots are smaller because less states are that far past their order.
    • I’m working on how to add a baseline to this chart to compare to states without orders, but that’s challenging because there’s no way to fully align timing.